Every day, millions of people log in to their computers using an associated password and username. By logging in and using such personalized information, the presence or absence of the person at a computer terminal can be determined. In addition, presence or absence of a person can be determined through a phone system. For instance, calls made by a person can be used to automatically detect presence of the caller's location.
Because these detection devices have limited ranges, however, other devices have been used for locating a person of interest. Motion sensor systems, through infrared technology, can determine the presence or absence of a person by detecting movements within a limited range. Global positioning systems (GPS), often provided in many cell phones, can also be used to determine the location of a person. Through these global positioning systems, latitude, longitude, and even the elevation of the person can be determined. In other applications, a wireless fidelity (WiFi) detector can be used. While providing a greater area for detection, these detectors often provide uncertain and ambiguous information.
Recently, “availability” features were introduced into presence and absence determination systems. Availability features provide the user with options describing their current status. Namely, a user could be “unavailable,” “available,” “busy,” “in a meeting,” “on a call,” etc. As an illustrative example, systems would consider a user “unavailable” if the computer system failed to detect mouse or keyboard movements for a prolonged period of time. Systems were also programmed to go “busy” when associated applications, such as electronic calendars, indicated so. By using the availability feature, other parties interested in the whereabouts of the user would be able to check the user's status.
Nevertheless, these systems did not take into account detectors such as the GPS and WiFi detector as provided above and were only related to determining whether the person of interest was within the immediate area. Furthermore, previous systems did not handle estimated locations in which a person can be found. These previous systems did not provide ways to identify locations in a manner which were suited to policies and applications that were applicable to various forms of human interaction. In addition, previous systems did not allow locations for the various forms of human interaction to propagate in a manner such to be combined with the various other forms of human interaction to provide a more deterministic result. Therefore, a need exists to provide a location detection and management system which can account for uncertainties provided by detectors as well as overcoming limitations present within today's systems.